02938ntm a2200325Ia 4500 318196 20260707210607.0 051012s2018 xx a bm 000 0 eng d ORE ORE OREV LD4330 Mabele, Leonard Omung'ala Mabele, Leonard Omung'ala. Leveraging TV white apace to monitor game conservation environments / by Leonard Omung'ala Mabele. c2018. xx leaves : ill. ; 29 cm. Printout. Thesis ()--Oregon State University, . Installation of camera-traps by the conservancies has been gaining interest in the recent years here in Kenya. This is due to the increased scientific need to carry out wildlife research and also monitor the movement patterns of the wild game as a way of helping to address issues such as human-wildlife conflict and poaching. This is also gaining traction by the safari camps to enhance customer experience. The implementation of these camera-traps poses a limitation of remotely accessing the camera feeds. This is majorly caused by a challenge of connectivity as many of these game environments are located in rural environments of Kenya. The focus of this study was to find out and establish the best approach of implementing a camera-trap that allows remote access of feeds in the game environments while leveraging on the connectivity that can be provided through deployment of Television (TV) White Space network. Through the use of questionnaires, an online survey was conducted in a select conservancy and a safari camp to investigate the challenges and the technology state within these environments that limit the adoption of networked game cameras. Various secondary sources were also studied to understand the existing connectivity technologies in the realm of the Internet of Things (IoT). The study used a combination of hardware and software technologies in realising the model in a TV White Space environment. A networked game camera prototype that delivers video feeds on a remote mobile interface was developed. The camera prototype utilised a programmed Raspberry Pi camera and the System-On-Chip to relay the gathered feeds in real-time to the mobile interface. The mobile interface developed in this case was an Android-based mobile-web. This was tested by ordinary users in a Wi-Fi environment, TV White Space connectivity experts and conservation officers. Also available on the World Wide Web. Includes bibliographical references (leaves - ). Internet of Things. 1388 Machine to Machine. 415112 M2M. 415113 Raspberry Pi. 415114 TV White Space. 407348 Dynamic Spectrum Access. 415115 http://hdl.handle.net/11071/6175 TH 318196 289452